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David Rosenberger

Showing results (1-10 of 10) with videos related to

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Methods in Enzymology|July 18, 2024
Dynamic framework for large-scale modeling of membranes and peripheral proteinsMohsen Sadeghi, David Rosenberger
Physical Review. E|June 20, 2019
Relative entropy indicates an ideal concentration for structure-based coarse graining of binary mixturesDavid Rosenberger, Nico F A van der Vegt
Physical Chemistry Chemical Physics : PCCP|February 17, 2018
Addressing the temperature transferability of structure based coarse graining modelsDavid Rosenberger, Nico F A van der Vegt
The Journal of Physical Chemistry. B|April 2, 2021
Modeling of Peptides with Classical and Novel Machine Learning Force Fields: A ComparisonDavid Rosenberger, Justin S Smith, Angel E Garcia
Physical Review. E|May 20, 2022
Machine learning of consistent thermodynamic models using automatic differentiationDavid Rosenberger, Kipton Barros, Timothy C Germann, et al.
The Journal of Physical Chemistry. B|December 20, 2018
Phase Equilibria Modeling with Systematically Coarse-Grained Models-A Comparative Study on State Point TransferabilityGregor Deichmann, Marco Dallavalle, David Rosenberger, et al.
Journal of Chemical Theory and Computation|April 18, 2019
Transferability of Local Density-Assisted Implicit Solvation Models for Homogeneous Fluid MixturesDavid Rosenberger, Tanmoy Sanyal, M Scott Shell, et al.
ACS Central Science|February 27, 2023
Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular KineticsWangfei Yang, Clark Templeton, David Rosenberger, et al.
Nature Communications|November 10, 2025
Peering inside the black box by learning the relevance of many-body functions in neural network potentialsKlara Bonneau, Jonas Lederer, Clark Templeton, et al.
Small (Weinheim an Der Bergstrasse, Germany)|September 18, 2025
Mechanochemically Synthesized Covalent Organic Framework Effectively Captures PFAS ContaminantsMaroof Arshadul Hoque, Thomas Sommerfeld, Jan Lisec, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Methods in Enzymology|July 18, 2024
Dynamic framework for large-scale modeling of membranes and peripheral proteinsMohsen Sadeghi, David Rosenberger
Physical Review. E|June 20, 2019
Relative entropy indicates an ideal concentration for structure-based coarse graining of binary mixturesDavid Rosenberger, Nico F A van der Vegt
Physical Chemistry Chemical Physics : PCCP|February 17, 2018
Addressing the temperature transferability of structure based coarse graining modelsDavid Rosenberger, Nico F A van der Vegt
The Journal of Physical Chemistry. B|April 2, 2021
Modeling of Peptides with Classical and Novel Machine Learning Force Fields: A ComparisonDavid Rosenberger, Justin S Smith, Angel E Garcia
Physical Review. E|May 20, 2022
Machine learning of consistent thermodynamic models using automatic differentiationDavid Rosenberger, Kipton Barros, Timothy C Germann, et al.
The Journal of Physical Chemistry. B|December 20, 2018
Phase Equilibria Modeling with Systematically Coarse-Grained Models-A Comparative Study on State Point TransferabilityGregor Deichmann, Marco Dallavalle, David Rosenberger, et al.
Journal of Chemical Theory and Computation|April 18, 2019
Transferability of Local Density-Assisted Implicit Solvation Models for Homogeneous Fluid MixturesDavid Rosenberger, Tanmoy Sanyal, M Scott Shell, et al.
ACS Central Science|February 27, 2023
Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular KineticsWangfei Yang, Clark Templeton, David Rosenberger, et al.
Nature Communications|November 10, 2025
Peering inside the black box by learning the relevance of many-body functions in neural network potentialsKlara Bonneau, Jonas Lederer, Clark Templeton, et al.
Small (Weinheim an Der Bergstrasse, Germany)|September 18, 2025
Mechanochemically Synthesized Covalent Organic Framework Effectively Captures PFAS ContaminantsMaroof Arshadul Hoque, Thomas Sommerfeld, Jan Lisec, et al.
Pageof 1